U.S. patent application number 15/664971 was filed with the patent office on 2019-01-31 for dynamic self-capacitive measurement acquisition.
The applicant listed for this patent is Synaptics Incorporated. Invention is credited to Matthew Stevenson.
Application Number | 20190034028 15/664971 |
Document ID | / |
Family ID | 65038595 |
Filed Date | 2019-01-31 |
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United States Patent
Application |
20190034028 |
Kind Code |
A1 |
Stevenson; Matthew |
January 31, 2019 |
DYNAMIC SELF-CAPACITIVE MEASUREMENT ACQUISITION
Abstract
Sensor circuitry is configured to perform, for a sensing frame,
mutual capacitive sensing to obtain mutual capacitive measurements,
and perform, for the sensing frame, first self-capacitive sensing
to obtain first self-capacitive measurements, and perform second
self-capacitive sensing to obtain a second self-capacitive
measurements. Processing circuitry is connected to the sensor
circuitry and is configured to detect an inconsistency between the
mutual capacitive measurements and the first self-capacitive
measurements, and halt, in response to detecting the inconsistency,
a second sensing frame to trigger performing the second
self-capacitive sensing. The second sensing frame is subsequent to
the first sensing frame. The processing circuitry is further
configured to determine intermittent interference using the first
self-capacitive measurements and the second self-capacitive
measurements.
Inventors: |
Stevenson; Matthew; (San
Jose, CA) |
|
Applicant: |
Name |
City |
State |
Country |
Type |
Synaptics Incorporated |
SanJose |
CA |
US |
|
|
Family ID: |
65038595 |
Appl. No.: |
15/664971 |
Filed: |
July 31, 2017 |
Current U.S.
Class: |
1/1 |
Current CPC
Class: |
G06F 3/04186 20190501;
G06F 3/0418 20130101; G06F 3/0446 20190501; G06F 3/044
20130101 |
International
Class: |
G06F 3/041 20060101
G06F003/041; G06F 3/044 20060101 G06F003/044 |
Claims
1. A processing system for interference management, comprising:
sensor circuitry configured to: perform, for a first sensing frame,
a mutual capacitive sensing to obtain a plurality of mutual
capacitive measurements, perform, for the first sensing frame, a
first self-capacitive sensing to obtain a first plurality of
self-capacitive measurements, and perform a second self-capacitive
sensing to obtain a second plurality of self-capacitive
measurements; and processing circuitry coupled to the sensor
circuitry and configured to: detect a first inconsistency between
the plurality of mutual capacitive measurements and the first
plurality of self-capacitive measurements, halt, in response to
detecting the first inconsistency, a second sensing frame to
trigger performing the second self-capacitive sensing, the second
sensing frame being subsequent to the first sensing frame, and
determine intermittent interference using the first plurality of
self-capacitive measurements and the second plurality of
self-capacitive measurements.
2. The processing system of claim 1, wherein the sensor circuitry
is further configured to: perform third self-capacitive sensing to
obtain a third plurality of self-capacitive measurements; and
wherein the processing circuitry is further configured to: trigger
performing the third self-capacitive sensing in response to
detecting intermittent interference, compare the third plurality of
self-capacitive measurements with the plurality of mutual
capacitive measurements, and detect a consistency when comparing
the third plurality of self-capacitive measurements with the
plurality of mutual capacitive measurements.
3. The processing system of claim 2, wherein the processing
circuitry is further configured to: determine, in response to
detecting the consistency, positional information for any input
object in a sensing region using the third plurality of
self-capacitive measurements and the plurality of mutual capacitive
measurements.
4. The processing system of claim 1, wherein the sensor circuitry
is further configured to: perform third self-capacitive sensing to
obtain a third plurality of self-capacitive measurements; and
wherein the processing circuitry is connected to the sensor
circuitry and configured to: trigger performing the third
self-capacitive sensing in response to detecting interference,
compare the third plurality of self-capacitive measurements with
the plurality of mutual capacitive measurements, and detect a
second inconsistency between the third plurality of self-capacitive
measurements and the plurality of mutual capacitive
measurements.
5. The processing system of claim 4, wherein the processing
circuitry is further configured to: compare the third plurality of
self-capacitive measurements with the second plurality of
self-capacitive measurements, detect a consistency between the
third plurality of self-capacitive measurements and the second
plurality of self-capacitive measurements, and perform baseline
error mitigation based on detecting the second inconsistency and
detecting the consistency.
6. The processing system of claim 4, wherein the processing
circuitry is further configured to: compare the third plurality of
self-capacitive measurements with the second plurality of
self-capacitive measurements, and detect a third inconsistency
between the third plurality of self-capacitive measurements and the
second plurality of self-capacitive measurements.
7. The processing system of claim 6, wherein the processing
circuitry is further configured to: perform intermittent
interference mitigation based on detecting the third
inconsistency.
8. The processing system of claim 7, wherein performing the
intermittent interference mitigation comprises changing a frequency
of a subsequent self-capacitive sensing from a frequency used to
perform the first self-capacitive sensing.
9. A method for interference management, comprising: performing,
for a first sensing frame, a mutual capacitive sensing to obtain a
plurality of mutual capacitive measurements; performing, for the
first sensing frame, a first self-capacitive sensing to obtain a
first plurality of self-capacitive measurements; detecting a first
inconsistency between the plurality of mutual capacitive
measurements and the first plurality of self-capacitive
measurements; halting, in response to detecting the first
inconsistency, a second sensing frame to trigger performing a
second self-capacitive sensing, the second sensing frame being
subsequent to the first sensing frame; performing the second
self-capacitive sensing to obtain a second plurality of
self-capacitive measurements; and determine intermittent
interference using the first plurality of self-capacitive
measurements and the second plurality of self-capacitive
measurements.
10. The method of claim 9, further comprising: triggering
performing a third self-capacitive sensing in response to detecting
interference; performing the third self-capacitive sensing to
obtain a third plurality of self-capacitive measurements; comparing
the third plurality of self-capacitive measurements with the
plurality of mutual capacitive measurements; and detecting a
consistency when comparing the third plurality of self-capacitive
measurements with the plurality of mutual capacitive
measurements.
11. The method of claim 9, further comprising: determining, in
response to detecting the consistency, positional information for
any input object in a sensing region using the third plurality of
self-capacitive measurements and the plurality of mutual capacitive
measurements.
12. The method of claim 9, further comprising: triggering
performing third self-capacitive sensing in response to detecting
interference; performing the third self-capacitive sensing to
obtain a third plurality of self-capacitive measurements; comparing
the third plurality of self-capacitive measurements with the
plurality of mutual capacitive measurements; and detecting a second
inconsistency between the third plurality of self-capacitive
measurements and the plurality of mutual capacitive
measurements.
13. The method of claim 12, further comprising: comparing the third
plurality of self-capacitive measurements with the second plurality
of self-capacitive measurements; detecting a consistency between
the third plurality of self-capacitive measurements and the second
plurality of self-capacitive measurements; and performing baseline
error mitigation based on detecting the second inconsistency and
detecting the consistency.
14. The method of claim 12, further comprising: comparing the third
plurality of self-capacitive measurements with the second plurality
of self-capacitive measurements; and detecting a third
inconsistency between the third plurality of self-capacitive
measurements and the second plurality of self-capacitive
measurements.
15. The method of claim 14, further comprising: performing
intermittent interference mitigation based on detecting the third
inconsistency.
16. The method of claim 15, wherein performing the intermittent
interference mitigation comprises changing a frequency of
subsequent self-capacitive sensing from a frequency used to perform
the first self-capacitive sensing.
17. An input device for interference management, comprising: a
plurality of sensor electrodes configured to acquire a plurality of
mutual capacitive measurements and a first plurality of
self-capacitive measurements of a sensing region; and a processing
system coupled to the plurality of sensor electrodes and configured
to: perform, for a first sensing frame, a mutual capacitive sensing
to obtain the plurality of mutual capacitive measurements, perform,
for the first sensing frame, a first self-capacitive sensing to
obtain the first plurality of self-capacitive measurements, detect
a first inconsistency between the plurality of mutual capacitive
measurements and the first plurality of self-capacitive
measurements, halt, in response to detecting the first
inconsistency, a second sensing frame to trigger performing a
second self-capacitive sensing, the second sensing frame being
subsequent to the first sensing frame, perform the second
self-capacitive sensing to obtain a second plurality of
self-capacitive measurements, and determine intermittent
interference using the first plurality of self-capacitive
measurements and the second plurality of self-capacitive
measurements.
18. The input device of claim 17, wherein the processing system is
further configured to: trigger performing a third self-capacitive
sensing in response to detecting intermittent interference, perform
the third self-capacitive sensing to obtain a third plurality of
self-capacitive measurements, compare the third plurality of
self-capacitive measurements with the plurality of mutual
capacitive measurements, and detect a consistency when comparing
the third plurality of self-capacitive measurements with the
plurality of mutual capacitive measurements.
19. The input device of claim 17, wherein the processing system is
further configured to: trigger performing third self-capacitive
sensing in response to detecting interference, perform the third
self-capacitive sensing to obtain a third plurality of
self-capacitive measurements, compare the third plurality of
self-capacitive measurements with the plurality of mutual
capacitive measurements, and detect a second inconsistency between
the third plurality of self-capacitive measurements and the
plurality of mutual capacitive measurements.
20. The input device of claim 19, wherein the processing system is
further configured to: compare the third plurality of
self-capacitive measurements with the second plurality of
self-capacitive measurements, and detect a third inconsistency
between the third plurality of self-capacitive measurements and the
second plurality of self-capacitive measurements.
Description
FIELD
[0001] This invention generally relates to electronic devices, and,
more specifically, to proximity sensor devices.
BACKGROUND
[0002] Input devices, including proximity sensor devices (e.g.,
touchpads or touch sensor devices), are widely used in a variety of
electronic systems. A proximity sensor device may include a sensing
region, often demarked by a surface, in which the proximity sensor
device determines the presence, location and/or motion of one or
more input objects. Proximity sensor devices may be used to provide
interfaces for the electronic system. For example, proximity sensor
devices may be used as input devices for larger computing systems
(e.g., opaque touchpads integrated in, or peripheral to, notebook
or desktop computers). Proximity sensor devices are also often used
in smaller computing systems (e.g., touch screens integrated in
cellular phones).
[0003] Proximity sensor devices are subject to interference from a
variety of external sources. Interference is the presence of noise
in the sensing region that impedes the detection of input objects.
For example, interference may be due to the display, through input
objects at other locations, and other conductive sources.
Interference may be persistent or intermittent. The presence of
interference impacts the input device's ability to accurately
detect and determine positional information for input objects.
Thus, interference is managed. The technique to manage interference
is dependent on whether the interference is persistent or
intermittent.
SUMMARY
[0004] Dynamic self-capacitive measurement acquisition is disclosed
for interference management. Sensor circuitry is configured to
perform, for a sensing frame, mutual capacitive sensing to obtain
mutual capacitive measurements, and perform, for the sensing frame,
first self-capacitive sensing to obtain first self-capacitive
measurements, and perform second self-capacitive sensing to obtain
a second self-capacitive measurements. Processing circuitry is
coupled to the sensor circuitry and is configured to detect an
inconsistency between the mutual capacitive measurements and the
first self-capacitive measurements, and halt, in response to
detecting the inconsistency, a second sensing frame to trigger
performing the second self-capacitive sensing. The second sensing
frame is subsequent to the first sensing frame. The processing
circuitry is further configured to determine intermittent
interference using the first self-capacitive measurements and the
second self-capacitive measurements.
[0005] A method for dynamic self-capacitive measurement acquisition
is disclosed for interference management. The method includes
performing, for a sensing frame, mutual capacitive sensing to
obtain mutual capacitive measurements, and performing, for the
sensing frame, first self-capacitive sensing to obtain first
self-capacitive measurements. The method further includes detecting
an inconsistency between the mutual capacitive measurements and the
first self-capacitive measurements, and halting, in response to
detecting the inconsistency, a second sensing frame to trigger
performing the second self-capacitive sensing. The second sensing
frame is subsequent to the first sensing frame. The method further
includes performing second self-capacitive sensing to obtain a
second self-capacitive measurements, and determine intermittent
interference using the first self-capacitive measurements and the
second self-capacitive measurements.
[0006] An input device for dynamic self-capacitive measurement
acquisition is disclosed for interference management. The input
device includes sensor electrodes configured to acquire a
measurements of a sensing region using a plurality of sensor
electrodes and a processing system. The processing system is
configured to perform, for a sensing frame, mutual capacitive
sensing to obtain mutual capacitive measurements, and perform, for
the sensing frame, first self-capacitive sensing to obtain first
self-capacitive measurements. The processing system is further
configured to detect an inconsistency between the mutual capacitive
measurements and the first self-capacitive measurements, and halt,
in response to detecting the inconsistency, a second sensing frame
to trigger performing the second self-capacitive sensing. The
second sensing frame is subsequent to the first sensing frame. The
processing system is further configured to perform second
self-capacitive sensing to obtain a second self-capacitive
measurements, and determine intermittent interference using the
first self-capacitive measurements and the second self-capacitive
measurements.
[0007] Other aspects of the technology will be apparent from the
following description and the appended claims.
BRIEF DESCRIPTION OF DRAWINGS
[0008] Exemplary embodiments of the present technology will
hereinafter be described in conjunction with the appended drawings,
where like designations denote like elements.
[0009] FIG. 1 is a block diagram of an example system that includes
an input device in accordance with an embodiment of the
disclosure;
[0010] FIG. 2 shows a schematic diagram of operating sensor
circuitry and processing circuitry in accordance with one or more
embodiments of the disclosure; and
[0011] FIG. 3 shows a flowchart for interference management in
accordance with one or more embodiments.
[0012] FIG. 4 shows a flowchart in accordance with one or more
embodiments of the disclosure.
DETAILED DESCRIPTION
[0013] The following detailed description is merely exemplary in
nature, and is not intended to limit the invention or the
application and uses of the invention. Furthermore, there is no
intention to be bound by any expressed or implied theory presented
in the preceding technical field, background, brief summary or the
following detailed description.
[0014] In the following detailed description of embodiments of the
disclosure, numerous specific details are set forth in order to
provide a more thorough understanding of the disclosure. However,
it will be apparent to one of ordinary skill in the art that the
disclosure may be practiced without these specific details. In
other instances, well-known features have not been described in
detail to avoid unnecessarily complicating the description.
[0015] Throughout the application, ordinal numbers (e.g., first,
second, third, etc.) may be used as an adjective for an element
(i.e., any noun in the application). The use of ordinal numbers is
not to imply or create any particular ordering of the elements nor
to limit any element to being only a single element unless
expressly disclosed, such as by the use of the terms "before",
"after", "single", and other such terminology. Rather, the use of
ordinal numbers is to distinguish between the elements. By way of
an example, a first element is distinct from a second element, and
the first element may encompass more than one element and succeed
(or precede) the second element in an ordering of elements.
[0016] Various embodiments of the present disclosure provide input
devices and methods that facilitate improved usability. In
particular, one or more embodiments are directed to interference
management in accordance with one or more embodiments of the
disclosure. Interference is an undesirable electrical disturbance
that may cause incorrect detection of input objects in a sensing
region of a capacitive input device. Interference impedes the
detection of input objects. Interference may be in the form of
persistent interference or intermittent interference. Persistent
interference is interference that lasts over a period of time
whereas intermittent interference occurs at irregular or sporadic
intervals that is discontinuous. One or more embodiments provide a
technique for differentiating between persistent interference and
intermittent interference in self-capacitive sensing, and may
further correct the interference based on the type of
interference.
[0017] In one or more embodiments, a sensing frame is obtained. The
sensing frame includes obtaining self-capacitive measurements and
mutual capacitive measurements. The sensing frame is processed
while another sensing frame is obtained, and if the self-capacitive
measurements do not match the mutual capacitive measurements, then
the subsequent sensing frame is halted and new self-capacitive
measurements are obtained. The sets of self-capacitive measurements
are compared to determine whether the interference is persistent or
intermittent, and the corresponding correction applied.
[0018] Turning now to the figures, FIG. 1 shows a block diagram of
an exemplary input device (100), in accordance with embodiments of
the disclosure. The input device (100) may be configured to provide
input to an electronic system (not shown for simplicity). As used
in this document, the term "electronic system" (or "electronic
device") broadly refers to any system capable of electronically
processing information. Examples of electronic systems may include
personal computers of all sizes and shapes (e.g., desktop
computers, laptop computers, netbook computers, tablets, web
browsers, e-book readers, and personal digital assistants (PDAs)),
composite input devices (e.g., physical keyboards, joysticks, and
key switches), data input devices (e.g., remote controls and mice),
data output devices (e.g., display screens and printers), remote
terminals, kiosks, video game machines (e.g., video game consoles,
portable gaming devices, and the like), communication devices
(e.g., cellular phones, such as smart phones), and media devices
(e.g., recorders, editors, and players such as televisions, set-top
boxes, music players, digital photo frames, and digital cameras).
Additionally, the electronic system could be a host or a slave to
the input device.
[0019] The input device (100) may be implemented as a physical part
of the electronic system. In the alternative, the input device
(100) may be physically separate from the electronic system. The
input device (100) may be coupled to (and communicate with)
components of the electronic system using various wired or wireless
interconnections and communication technologies, such as buses and
networks. Example technologies may include Inter-Integrated Circuit
(I2C), Serial Peripheral Interface (SPI), PS/2, Universal Serial
Bus (USB), Bluetooth.RTM., Infrared Data Association (IrDA), and
various radio frequency (RF) communication protocols defined by the
IEEE 802.11 or other standards.
[0020] In the example of FIG. 1, the input device (100) may
correspond to a proximity sensor device (such as a "touchpad" or a
"touch sensor device") configured to sense input provided by one or
more input objects (140) in a sensing region (120). Example input
objects include fingers and styli. The sensing region (120) may
encompass any space above, around, in and/or near the input device
(100) in which the input device (100) is able to detect user input
(e.g., provided by one or more input objects (140)). The sizes,
shapes, and locations of particular sensing regions may vary
depending on actual implementations.
[0021] In some embodiments, the sensing region (120) extends from a
surface of the input device (100) in one or more directions into
space, for example, until a signal-to-noise ratio falls below a
threshold suitable for object detection. For example, the distance
to which this sensing region (120) extends in a particular
direction, in various embodiments, may be on the order of less than
a millimeter, millimeters, centimeters, or more, and may vary with
the type of sensing technology used and/or the accuracy desired. In
some embodiments, the sensing region (120) detects inputs involving
no physical contact with any surfaces of the input device (100),
contact with an input surface (e.g. a touch surface) of the input
device (100), contact with an input surface of the input device
(100) coupled with some amount of applied force or pressure, and/or
a combination thereof.
[0022] In various embodiments, input surfaces may be provided by
surfaces of a housing of the input device (100) within which the
sensor electrodes reside, by face sheets applied over the sensor
electrodes or any casings, etc. In some embodiments, the sensing
region (120) has a rectangular shape when projected onto an input
surface of the input device (100).
[0023] The input device (100) may utilize any combination of sensor
components and sensing technologies to detect user input in the
sensing region (120). The input device (100) includes one or more
sensing elements for detecting user input. As several non-limiting
examples, the input device (100) may use capacitive, elastive,
resistive, inductive, magnetic, acoustic, ultrasonic, optical,
and/or other suitable techniques.
[0024] Some implementations are configured to provide images that
span one, two, three, or higher-dimensional spaces. An image is a
collection of measurements of the sensing region where each
measurement corresponds to a particular position on the sensing
region. For example, in capacitive implementation, a capacitive
image has a capacitive measurement for each location of the sensing
region. Some implementations are configured to use and/or provide
projections of input along particular axes or planes. A projection
is an aggregation of measurements along the axis or plane. For
example, a projection may have multiple values, where each value is
along a first axis, and each value is a sum of the measurements
along a second axis. By way of a more specific example, a column
projection may have a single value for each row of a column, where
each single value corresponds to a sum of the measurement values
for the row. Further, some implementations may be configured to use
and/or provide a combination of one or more images and one or more
projections.
[0025] The input device (100) may utilize various sensing
technologies to detect user input. Example sending technologies may
include resistive, inductive, capacitive, elastive, magnetic,
acoustic, ultrasonic, and optical sensing technologies. In some
embodiments, the input device (100) may include one or more sensing
elements configured to implement the various sensing
technologies.
[0026] In some embodiments, the input device (100) may implement
resistive sensing technologies to detect user input. For example,
the sensing region (120) may be formed by a flexible and conductive
first layer separated by one or more spacer elements from a
conductive second layer. The sensing region (120) may detect user
input by creating one or more voltage gradients across the layers
and sensing when the first layer is brought in contact with the
second layer. More specifically, pressing the flexible first layer
may deflect it sufficiently to create electrical contact between
the layers, resulting in voltage outputs reflective of the point(s)
of contact between the layers. These voltage outputs may be used to
determine positional information of the detected inputs.
[0027] In other embodiments, the input device (100) may utilize
inductive sensing technologies to detect user inputs. For example,
the sensing region (120) may include one or more sensing elements
configured to pick up loop currents induced by a resonating coil or
pair of coils. The input device (100) may then detect user input
based on a combination of the magnitude, phase, and/or frequency of
the currents. The characteristics of the loop currents may further
be used to determine positional information about the detected
inputs.
[0028] In some embodiments, the input device (100) may utilize
capacitive sensing technologies to detect user input. For example,
the sensing region (120) may input one or more capacitive sensing
elements (e.g., sensor electrodes) to create an electric field. The
input device (100) may detect inputs based on changes in the
capacitance of the sensor electrodes. More specifically, an object
in contact with (or in close proximity to) the electric field may
cause changes in the voltage and/or current in the sensor
electrodes. Such changes in voltage and/or current may be detected
as "signals" indicative of user input. The sensor electrodes may be
arranged in arrays or other regular or irregular patterns of
capacitive sensing elements to create electric fields. In some
implementations, some sensing elements may be ohmically shorted
together to form larger sensor electrodes. Some capacitive sensing
technologies may utilize resistive sheets that provide a uniform
layer of resistance.
[0029] Some capacitive sensing technologies may be based on
"self-capacitance" (also referred to as "absolute capacitance")
and/or mutual capacitance (Also referred to as "transcapacitance").
Absolute capacitance sensing methods detect changes in the
capacitive coupling between sensor electrodes and an input object.
Absolute capacitance sensing measures the self-capacitance of the
sensor electrode, where the self-capacitance is the amount of
electric charge that must be added to a sensor electrode to raise
the sensor electrode's electric potential by one unit (e.g., one
volt). The self-capacitance of the sensor electrode changes when an
input object is proximate to the sensor electrode. For example, an
input object near the sensor electrodes may alter the electric
field near the sensor electrodes, thus changing the measured
capacitive coupling. In some embodiments, the input device (100)
may implement by modulating sensor electrodes with respect to a
reference voltage (e.g., system ground), and detecting the
capacitive coupling between the sensor electrodes and input
objects. The reference voltage may be a substantially constant
voltage, a varying voltage, or corresponds to a system ground.
Measurements acquired using absolute capacitance sensing methods
may be referred to as absolute capacitive measurements.
[0030] Transcapacitance sending methods detect changes in the
capacitive coupling between sensor electrodes. For example, an
input object near the sensor electrodes may alter the electric
field between the sensor electrodes, thus changing the measured
capacitive coupling of the sensor electrodes. In some embodiments,
the input device (100) may implement transcapacitance sensing by
detecting the capacitive coupling between one or more transmitter
sensor electrodes (also "transmitter electrodes" or "transmitter")
and one or more receiver sensor electrodes (also "receiver
electrodes" or "receiver"). Signals on the transmitter sensor
electrodes may be modulated relative to a reference voltage (e.g.,
system ground) to transmit transmitter signals while receiver
sensor electrodes may be held at a substantially constant voltage
relative to the reference voltage to receive resulting signals. The
reference voltage may be a substantially constant voltage or may be
system ground. The resulting signal may be affected by
environmental interference (e.g., other electromagnetic signals) as
well as input objects in contact with, or in close proximity to,
the sensor electrodes. Sensor electrodes may be dedicated
transmitters or receivers, or may be configured to both transmit
and receive. Measurements acquired using mutual capacitance sensing
methods may be referred to as mutual capacitance measurements.
[0031] Further, the sensor electrodes may be of varying shapes
and/or sizes. The same shapes and/or sizes of sensor electrodes may
or may not be in the same groups. For example, in some embodiments,
receiver electrodes may be of the same shapes and/or sizes while,
in other embodiments, receiver electrodes may be varying shapes
and/or sizes.
[0032] The processing system (110) may be configured to operate the
hardware of the input device (100) to detect input in the sensing
region (120). The processing system (110) may include parts of, or
all of, one or more integrated circuits (ICs) and/or other
circuitry components. For example, a processing system for a mutual
capacitance sensor device may include transmitter circuitry
configured to transmit signals with transmitter sensor electrodes,
and/or receiver circuitry configured to receive signals with
receiver sensor electrodes. Further, a processing system for an
absolute capacitance sensor device may include driver circuitry
configured to drive absolute capacitance signals onto sensor
electrodes, and/or receiver circuitry configured to receive signals
with those sensor electrodes. In one or more embodiments, a
processing system for a combined mutual and absolute capacitance
sensor device may include any combination of the above described
mutual and absolute capacitance circuitry. In some embodiments, the
processing system (110) also includes electronically-readable
instructions, such as firmware code, software code, and/or the
like. In some embodiments, components composing the processing
system (110) are located together, such as near sensing element(s)
of the input device (100). In other embodiments, components of
processing system (110) are physically separate with one or more
components close to the sensing element(s) of the input device
(100), and one or more components elsewhere. For example, the input
device (100) may be a peripheral coupled to a computing device, and
the processing system (110) may include software configured to run
on a central processing unit of the computing device and one or
more ICs (perhaps with associated firmware) separate from the
central processing unit. As another example, the input device (100)
may be physically integrated in a mobile device, and the processing
system (110) may include circuits and firmware that are part of a
main processor of the mobile device. In some embodiments, the
processing system (110) is dedicated to implementing the input
device (100). In other embodiments, the processing system (110)
also performs other functions, such as operating display screens,
driving haptic actuators, etc.
[0033] The processing system (110) may be implemented as a set of
modules that handle different functions of the processing system
(110). Each module may be implemented in hardware, firmware,
software, or a combination thereof. In some embodiments, the
processing system (110) may include processing circuitry (150)
configured to determine when at least one input object is in a
sensing region, determine signal to noise ratio, determine
positional information of an input object, identify a gesture,
determine an action to perform based on the gesture, a combination
of gestures or other information, and/or perform other operations.
In some embodiments, the processing system (110) may include sensor
circuitry (160) configured to drive the sensing elements to
transmit transmitter signals and receive the resulting signals. The
processing circuitry (150) and the sensor circuitry (160) may be
coupled. In some embodiments, the sensor circuitry (160) may
include sensory circuitry that is coupled to the sensing elements.
The sensory circuitry may include, for example, a transmitter
module including transmitter circuitry that is coupled to a
transmitting portion of the sensing elements and a receiver module
including receiver circuitry coupled to a receiving portion of the
sensing elements.
[0034] Although FIG. 1 shows only processing circuitry (150) and
sensor circuitry (160), alternative or additional modules may exist
in accordance with one or more embodiments of the disclosure. Such
alternative or additional modules may correspond to distinct
modules or sub-modules than one or more of the modules discussed
above. Example alternative or additional modules include hardware
operation modules for operating hardware such as sensor electrodes
and display screens, data processing modules for processing data
such as sensor signals and positional information, reporting
modules for reporting information, and identification modules
configured to identify gestures, such as mode changing gestures,
and mode changing modules for changing operation modes. Further,
the various modules may be combined in separate integrated
circuits. For example, a first module may be comprised at least
partially within a first integrated circuit and a separate module
may be comprised at least partially within a second integrated
circuit. Further, portions of a single module may span multiple
integrated circuits. In some embodiments, the processing system as
a whole may perform the operations of the various modules.
[0035] In some embodiments, the processing system (110) responds to
user input (or lack of user input) in the sensing region (120)
directly by causing one or more actions. Example actions include
changing operation modes, as well as graphical user interface (GUI)
actions such as cursor movement, selection, menu navigation, and
other functions. In some embodiments, the processing system (110)
provides information about the input (or lack of input) to some
part of the electronic system (e.g. to a central processing system
of the electronic system that is separate from the processing
system (110), if such a separate central processing system exists).
In some embodiments, some part of the electronic system processes
information received from the processing system (110) to act on
user input, such as to facilitate a full range of actions,
including mode changing actions and GUI actions.
[0036] For example, in some embodiments, the processing system
(110) operates the sensing element(s) of the input device (100) to
produce electrical signals indicative of input (or lack of input)
in the sensing region (120). The processing system (110) may
perform any appropriate amount of processing on the electrical
signals in producing the information provided to the electronic
system. For example, the processing system (110) may digitize
analog electrical signals obtained from the sensor electrodes. As
another example, the processing system (110) may perform filtering
or other signal conditioning. As yet another example, the
processing system (110) may subtract or otherwise account for a
baseline, such that the information reflects a difference between
the electrical signals and the baseline. A baseline is an estimate
of the raw measurements of the sensing region when an input object
is not present. For example, a capacitive baseline is an estimate
of the background capacitance of the sensing region. Each sensing
element may have a corresponding individual value in the baseline.
As yet further examples, the processing system (110) may determine
positional information, recognize inputs as commands, recognize
handwriting, and the like.
[0037] "Positional information" as used herein broadly encompasses
absolute position, relative position, velocity, acceleration, and
other types of spatial information. Exemplary "zero-dimensional"
positional information includes near/far or contact/no contact
information. Exemplary "one-dimensional" positional information
includes positions along an axis. Exemplary "two-dimensional"
positional information includes motions in a plane. Exemplary
"three-dimensional" positional information includes instantaneous
or average velocities in space. Further examples include other
representations of spatial information. Historical data regarding
one or more types of positional information may also be determined
and/or stored, including, for example, historical data that tracks
position, motion, or instantaneous velocity over time.
[0038] In some embodiments, the input device (100) is implemented
with additional input components that are operated by the
processing system (110) or by some other processing system. These
additional input components may provide redundant functionality for
input in the sensing region (120), or some other functionality.
FIG. 1 shows buttons (130) near the sensing region (120) that may
be used to facilitate selection of items using the input device
(100). Other types of additional input components include sliders,
balls, wheels, switches, and the like. Conversely, in some
embodiments, the input device (100) may be implemented with no
other input components.
[0039] In some embodiments, the input device (100) includes a touch
screen interface, and the sensing region (120) overlaps at least
part of an active area of a display screen. For example, the input
device (100) may include substantially transparent sensor
electrodes overlaying the display screen and provide a touch screen
interface for the associated electronic system. The display screen
may be any type of dynamic display capable of displaying a visual
interface to a user, and may include any type of light emitting
diode (LED), organic LED (OLED), cathode ray tube (CRT), liquid
crystal display (LCD), plasma, electroluminescence (EL), or other
display technology. The input device (100) and the display screen
may share physical elements. For example, some embodiments may
utilize some of the same electrical components for displaying and
sensing. In various embodiments, one or more display electrodes of
a display device may be configured for both display updating and
input sensing. As another example, the display screen may be
operated in part or in total by the processing system (110).
[0040] While many embodiments are described in the context of a
fully-functioning apparatus, the mechanisms of are capable of being
distributed as a program product (e.g., software) in a variety of
forms. For example, the mechanisms of the disclosure may be
implemented and distributed as a software program on
information-bearing media that are readable by electronic
processors (e.g., non-transitory computer-readable and/or
recordable/writable information bearing media that is readable by
the processing system (110)). Additionally, the embodiments apply
equally regardless of the particular type of medium used to carry
out the distribution. For example, software instructions in the
form of computer readable program code to perform embodiments may
be stored, in whole or in part, temporarily or permanently, on a
non-transitory computer-readable storage medium. Examples of
non-transitory, electronically-readable media include various
discs, physical memory, memory, memory sticks, memory cards, memory
modules, and or any other computer readable storage medium.
Electronically-readable media may be based on flash, optical,
magnetic, holographic, or any other storage technology.
[0041] Although not shown in FIG. 1, the processing system, the
input device, and/or the host system may include one or more
computer processor(s), associated memory (e.g., random access
memory (RAM), cache memory, flash memory, etc.), one or more
storage device(s) (e.g., a hard disk, an optical drive such as a
compact disk (CD) drive or digital versatile disk (DVD) drive, a
flash memory stick, etc.), and numerous other elements and
functionalities. The computer processor(s) may be an integrated
circuit for processing instructions. For example, the computer
processor(s) may be one or more cores or micro-cores of a
processor. Further, one or more elements of one or more embodiments
may be located at a remote location and connected to the other
elements over a network. Further, embodiments may be implemented on
a distributed system having several nodes, where each portion of
the disclosure may be located on a different node within the
distributed system. In one embodiment, the node corresponds to a
distinct computing device. Alternatively, the node may correspond
to a computer processor with associated physical memory. The node
may alternatively correspond to a computer processor or micro-core
of a computer processor with shared memory and/or resources.
[0042] While FIG. 1 shows a configuration of components, other
configurations may be used without departing from the scope of the
disclosure. For example, various components may be combined to
create a single component. As another example, the functionality
performed by a single component may be performed by two or more
components.
[0043] FIG. 2 shows a schematic diagram of operating sensor
circuitry and processing circuitry in accordance with one or more
embodiments. As discussed above, the sensor circuitry is configured
to acquire measurements from the sensing region by driving sensor
electrodes or modulating sensor electrodes with respect to a
reference voltage. The value of the measurements may be affected by
the presence of any input objects in the sensing region and/or
interference, such as noise, in the sensing region. The processing
circuitry may process the measurements and determine positional
information of the input objects in the sensing region.
[0044] The left side of FIG. 2 illustrates the operation of the
sensor circuitry and the sensor electrodes (202). More
specifically, sensor circuitry of the input device captures the
sensing region on a per frame (e.g., frame n-1 (204), frame n
(206), frame n+1 (208)) basis. Each frame (e.g., frame n-1 (204),
frame n (206), frame n+1 (208)) represents a time window during
which a single capture of the status of the sensing region is
performed. The status of the sensing region may be, for example,
with respect to the presence of any input object. The time window
of the frame is of a size that may be perceived as instantaneous to
a human operator such that an input object may be approximated as
being stationary, or as being in a single position, in a frame. The
three collinear dots represent additional frames that may be
captured and/or processed before or after the frames shown in FIG.
2.
[0045] In one or more embodiments, after processing a frame, a
report may be generated and communicated to other components of the
processing system, input device, host system, or another device, or
any combination thereof. Each report may include positional
information regarding any input objects in the sensing region
during the frame, change in locations of input objects as compared
to one or more prior frames, relative position of an input object,
and so on.
[0046] During a single frame, mutual capacitive sensing (e.g.,
mutual capacitive sensing n-1 (210), mutual capacitive sensing n
(212), mutual capacitive sensing n+1 (214)), self-capacitive
sensing (e.g., self-capacitive sensing n-1 (216), self-capacitive
sensing n (218), self-capacitive sensing n+1 (220)), and,
optionally, noise bursts (e.g., noise bursts n-1 (222), noise
bursts n (224), noise bursts n+1 (226)) may be performed. During
mutual capacitive sensing, the sensor circuitry drives the
transmitter sensor electrodes with transmitter signals and receives
resulting signals with receiver transmitter electrodes. The
resulting signals (or mutual capacitance) correspond to the
capacitance between the transmitter electrodes and the receiver
electrodes as affected by the presence of any input object and
interference near intersection of respective transmitter electrode
and receiver electrode. A mutual capacitive image of the sensing
region may be generated using a mutual capacitive measurement at
each intersection of transmitter electrodes and receiver
electrodes.
[0047] Self-capacitance of the sensor electrodes may be determined
by self-capacitive sensing during which the sensor circuitry
modulates sensing signals on the sensor electrodes with respect to
a reference voltage. Based on the modulation, the sensor circuitry
can detect self-capacitive measurements of each sensor electrode.
The self-capacitance may be affected by the presence of input
objects in the sensing region and interference. In one or more
embodiments, self-capacitive sensing may create a self-capacitive
image or self-capacitive profiles of the sensing region. For
example, if the sensor electrodes are an advanced matrix pad (AMP)
sensor, then a separate sensor electrode may exist for each
location in a sensor grid on the sensing region. In such a
scenario, the self-capacitive image has a self-capacitive
measurement for each location of the grid. By way of another
example, a single separate sensor electrode may exist for each row
and each column of the sensing region. In such a scenario, each row
may have a single self-capacitive measurement in a first profile
and each column may have a single self-capacitive measurement value
in a second profile. Although the above is discussed with respect
to a grid pattern of sensor electrodes, other sensor electrode
patterns may be used. For example, irregular patterns and non-grid
configurations may be used.
[0048] Noise bursts may be used for noise measurement. During noise
bursts, the receiver electrodes receive resulting signals while
suspending transmission at the transmitter electrodes. Thus, only
receiver electrodes receive without the transmitter electrodes
transmitting. When noise bursts are performed, interference
affecting mutual capacitive measurements may be present without
showing the presence of input objects. Noise bursts may be
performed, for example, to select a frequency for transmission.
[0049] Although FIG. 2 shows a frame having an order of mutual
capacitive sensing, followed by noise bursts, followed by
self-capacitive sensing, the order may be different.
[0050] The right side of FIG. 2 shows operations of the processing
circuitry (230) in accordance with one or more embodiments. As
shown, the processing circuitry processes each frame (e.g.,
processing of frame n-1 (232), processing of frame n (234)) in
order. Processing each frame includes processing the mutual
capacitive measurements, the self-capacitive measurements and the
noise bursts. Processing the mutual capacitive measurements may
include subtracting a current mutual capacitive baseline from the
raw mutual capacitive measurements acquired by the sensor circuitry
to obtain delta mutual capacitive measurements.
[0051] The mutual capacitive baseline may be an estimation of the
background capacitance of the sensor electrodes when an input
object is not present. For example, the mutual capacitive baseline
may be an estimation of persistent noise in the sensing region that
affects the mutual capacitive measurements. Each measurement value
may have a corresponding baseline value in the baseline. The
corresponding baseline value may be subtracted from the raw
measurement value to obtain the delta measurement value. When the
mutual capacitive baseline is incorrect, an input object that is
present in the sensing region may not be detected by the processing
circuitry because the corresponding resulting delta mutual
capacitive measurements may not satisfy a detection threshold.
Similarly, an input object that is not actually present in the
sensing region may be detected by the processing circuitry because
the corresponding resulting delta mutual capacitive measurements
may falsely satisfy the detection threshold.
[0052] Processing of the mutual capacitive measurements may include
other spatial and/or temporal filters, generating projections,
identifying clusters of mutual capacitive measurements satisfying a
detection threshold and other processing.
[0053] Processing the self-capacitive measurements may include
subtracting a current self-capacitive baseline from the raw
self-capacitive measurements acquired by the sensor circuitry to
obtain delta self-capacitive measurements. Similar to mutual
capacitive baseline, the self-capacitive baseline may be an
estimation of the background capacitance of the sensor electrodes
when an input object is not present. For example, the
self-capacitive baseline is an estimation of persistent noise in
the sensing region that affects the self-capacitive measurements.
Each measurement value may have a corresponding baseline value in
the baseline. The corresponding baseline value may be subtracted
from the raw measurement value to obtain the delta measurement
value. When the self-capacitive baseline is incorrect, an input
object that is present in the sensing region may not be detected by
the processing circuitry because the corresponding resulting delta
self-capacitive measurements may not satisfy a detection threshold.
Similarly, an input object that is not actually present in the
sensing region may be detected by the processing circuitry because
the corresponding resulting delta self-capacitive measurements may
falsely satisfy the detection threshold. Processing of the
self-capacitive measurements may include other spatial and/or
temporal filters, identifying peak values satisfying a detection
threshold and other processing.
[0054] Processing a frame may further include comparing the mutual
capacitive measurements with the absolute capacitive measurements
as described below and in FIG. 3. The combination of mutual
capacitive measurements and absolute capacitive measurements may be
used for moisture touch detection, baseline error detection, low
ground mass correction, and other corrections. Moisture touch
detection is to detect the presence of one or more input objects
when moisture (e.g., water or other liquid) is on the sensing
region surface and affecting the resulting measurement values.
Baseline error correction is to correct when an absolute or mutual
capacitive baseline results in falsely detecting input objects or
failed to detect input objects. Low ground mass correction is to
detect that the input device is in a low ground mass state causing
the resulting signals and the corresponding measurements to be
unstable, and then applying a correction to each of the
measurements to detect an input object.
[0055] Further, noise bursts may be processed by using the
measurements from the noise bursts as an estimation of the noise
and adjusting the baselines or frequencies used for sensing
accordingly.
[0056] Although FIG. 2 shows processing a frame after the sensor
circuitry completes the frame, the processing may be partially
concurrent with generation of the frame by the sensor circuitry.
For example, once the sensor circuitry acquires the mutual
capacitive measurements, the processing circuitry may begin
processing the mutual capacitive measurements. As such, the start
of processing of the measurements may be performed as soon as the
inputs (e.g., corresponding measurements) to the type of processing
are received.
[0057] When a frame is processed by the processing circuitry, a
determination may be made whether the mutual capacitive
measurements and the self-capacitive measurements are consistent
(e.g., both indicate a presence of input object or lack thereof).
If inconsistent, then the processing circuitry is configured to
halt the sensor circuitry from obtaining the next frame and trigger
the sensor circuitry to obtain absolute capacitive measurements.
For example, if the sensor circuitry is in the process of obtaining
mutual capacitive measurements or noise burst measurements, the
sensor circuitry immediately stops obtaining the mutual capacitive
measurements or noise bursts and acquires the absolute capacitive
measurements. The sensor circuitry then provides the newly acquired
absolute capacitive measurements to the processing circuitry, which
performs the processing described in FIG. 3.
[0058] FIG. 3 shows a flowchart for interference management in
accordance with one or more embodiments. While the various steps in
this flowchart are presented and described sequentially, some or
all of the steps may be executed in different orders, may be
combined or omitted, and some or all of the steps may be executed
in parallel. Furthermore, the steps may be performed actively or
passively. For example, some steps may be performed using polling
or be interrupt driven in accordance with one or more embodiments
of the disclosure. By way of an example, determination steps may
not require a processor to process an instruction unless an
interrupt is received to signify that condition exists in
accordance with one or more embodiments of the disclosure. As
another example, determination steps may be performed by performing
a test, such as checking a data value to test whether the value is
consistent with the tested condition in accordance with one or more
embodiments of the disclosure.
[0059] In Step 301, mutual capacitive sensing is performed to
obtain mutual capacitive measurements using the sensor circuitry
and sensor electrodes as described above with reference to FIG.
2.
[0060] In Step 303, self-capacitive measurements sensing is
performed to obtain first self-capacitive measurements of the
sensing region using the sensor circuitry and the sensor electrodes
as described above with reference to FIG. 2. The self-capacitive
sensing in Step 303 and the mutual capacitive sensing in Step 301
are performed during the same frame of sensing. From the
self-capacitive sensing, self-capacitive measurements are acquired.
For the purposes of distinction from later acquired self-capacitive
measurements, the self-capacitive measurements obtained in Step 303
are referred to as first self-capacitive measurements.
[0061] In Step 305, an inconsistency is detected when comparing the
mutual capacitive measurements with the first self-capacitive
measurements in accordance with one or more embodiments of the
disclosure. For example, the mutual capacitive measurements and the
first self-capacitive measurements may be individually processed,
such as to account for a corresponding baseline and to perform
spatial and/or temporal filtering as described above with reference
to FIG. 2. For the purposes of simplifying the description, the
same terminology of mutual capacitive measurements and
self-capacitive measurements is used to refer to the measurements
before and after any preprocessing (e.g., to account for the
baseline). Unless explicitly specified using words, "raw" and
"delta", the corresponding measurements may be at any stage of
preprocessing.
[0062] Further, the mutual capacitive measurements and absolute
capacitive measurements may be compared with corresponding
detection thresholds. In some embodiments, because self-capacitive
sensing detects input objects at a greater distance from the sensor
electrode than mutual capacitive sensing, an artificially higher
detection threshold than the normal detection threshold may be set
for the self-capacitive measurements in order to disqualify
hovering objects and for the purposes of the consistency check.
Further, other techniques may be used to account for the greater
sensitivity of the self-capacitive sensing to input objects.
[0063] Locations of the input objects in the corresponding
capacitive measurements may be determined from the measurements
that satisfy the detection thresholds. Various techniques may be
used to determine the locations from the measurements satisfying
the detection thresholds, such as based on locations of peaks in
the measurements, number of adjacent measurements satisfying the
detection threshold, etc.
[0064] The comparison of the mutual capacitive measurements and
first self-capacitive measurements is performed to determine
whether any input objects detected in the mutual capacitive
measurements correspond to any input objects detected in the first
self-capacitive measurements. Multiple techniques may be used to
perform the comparison between sets of measurements (i.e., set of
mutual capacitive measurements and set of self-capacitive
measurements). Some of the techniques are described below.
[0065] In some embodiments, direct comparison can be made between a
self-capacitive image derived from self-capacitive measurements and
a mutual capacitive image derived from mutual capacitive
measurements. For example, for each identified location of an input
object, the location of the input object in the sensing region
determined from the mutual capacitive measurements is compared with
location of the input objects determined from the self-capacitive
measurements. If the locations match or are within a threshold
distance to each other, then the self-capacitive measurements and
the mutual capacitive measurements are deemed consistent. More
specifically, consistency is determined by both sets of
measurements indicating the same or substantially the same
locations of input objects. If an input object in an image does not
match a location of an input object in the other image, then the
mutual capacitive measurements and the self-capacitive measurements
may be deemed inconsistent.
[0066] In some embodiments, comparison may be made using
self-capacitive profiles. More specifically, the locations of the
input objects in the self-capacitive profiles are projected on the
sensing region. In the projection, a single self-capacitive
measurement is attributed to the entire length of the sensor
electrode from which the measurement is obtained. Thus, a location
of a possible input object is any location along the length of the
sensor electrode in the sensing region. For row/column sensor
electrodes, a location in the self-capacitive profile identifies an
entire row or column of the sensing region in which the input
object may be located. The intersection of the identified rows and
columns between the self-capacitive profiles identify the possible
locations in the sensing region in which the input object may be
located.
[0067] Continuing with the comparison using the self-capacitive
profiles, the comparison of the self-capacitive measurements and
the mutual capacitive measurements may be performed by determining
whether each location of an input object in the mutual capacitive
measurements is at an intersection of the projections. If an input
object is not located at an intersection, then the self-capacitive
measurements and mutual capacitive measurements may be determined
to be inconsistent. The comparison may further include determining
whether each projected location of an input object from the
self-capacitive measurements has at least one location of an input
object from the mutual capacitive measurements. If a projected
location of an input object from the self-capacitive measurements
does not have at least one location of an input object from the
mutual capacitive measurements, then the self-capacitive
measurements and the mutual capacitive measurements are
inconsistent. If each location of an input object in the mutual
capacitive measurements is at an intersection of the projections
and a projected location of an input object from the
self-capacitive measurements has at least one location of an input
object from the mutual capacitive measurements, then the
measurements may be deemed consistent.
[0068] In some embodiments, comparison may be made by projecting
locations of the input object detected in the mutual capacitive
image on the self-capacitive profiles. In the projection, a
location of an input object is attributed to both of the sensor
electrodes that form the capacitor used to identify the location.
Thus, a location in the mutual capacitive image identifies a
separate location in each self-capacitive profile. Comparison of
the self-capacitive measurements and the mutual capacitive
measurements may be performed by determining whether each location
of an input object in the projection is a location of the input
object in the self-capacitive profile and whether each location in
the self-capacitive profile is in the projection. If a location is
not in both the projection and the self-capacitive profile, then
the self-capacitive measurements and the mutual capacitive
measurements are inconsistent. If all locations are in both the
projection and the self-capacitive profile, then the
self-capacitive measurements and the mutual capacitive measurements
are consistent.
[0069] The above are only a few examples of determining whether
self-capacitive measurements and mutual capacitive measurements are
consistent. Other techniques for determining the consistency and
inconsistency between the self-capacitive measurements and mutual
capacitive measurements may be used without departing from the
scope of the disclosure.
[0070] In the example shown in FIG. 3, an inconsistency is detected
between the self-capacitive measurements and mutual capacitive
measurements in Step 305. Accordingly, in Step 307, a subsequent
sensing frame is halted in response to detecting the inconsistency
in order to obtain second self-capacitive measurements of the
sensing region by performing self-capacitive sensing. The
processing system triggers the sensor circuitry to stop the current
frame being performed by the sensor circuitry and to collect
absolute capacitive measurements. The trigger may be in the form of
a predefined signal from the processing circuitry to the sensor
circuitry.
[0071] In Step 309, intermittent interference is determined using
the first self-capacitive measurements and the second
self-capacitive measurements in accordance. The first
self-capacitive measurements and the second self-capacitive
measurements are compared. In some embodiments, the comparison may
be performed by determining whether the same location(s) of input
object(s) are in the first self-capacitive measurements and the
second self-capacitive measurements. Same locations are locations
that are within a threshold distance to each other.
[0072] In some embodiments, the comparison may be performed by
determining whether the geometric shape of the first
self-capacitive measurement and the second self-capacitive
measurements are within a threshold to each other. The geometric
shape refers to the shape of the measurements if the measurements
were plotted on a graph with one axis of the graph being the sensor
electrode axis and the other axis of the graph being the value of
the measurement axis. The geometric shapes may be compared without
plotting the self-capacitive measurements by comparing the slopes
between neighboring sensor electrodes. The slope may be determined
for a self-capacitive measurement to a neighboring self-capacitive
measurement (e.g., a self-capacitive measurement within a
pre-defined distance away). If the slopes are consistent between
the first self-capacitive measurements and the second
self-capacitive measurements, then the self-capacitive measurements
are determined to be consistent. If the slopes are not consistent,
then the self-capacitive measurements may be deemed
inconsistent.
[0073] The above are only a few examples of determining whether the
first self-capacitive measurements and second self-capacitive
measurements are consistent. Other techniques for determining the
consistency and inconsistency between the self-capacitive
measurements.
[0074] If the first self-capacitive measurements and the second
self-capacitive measurements are consistent, then persistent
interference may be detected. Persistent interference is due to a
continued error affecting the self-capacitive measurements.
Persistent interference may be managed by updating a baseline.
Persistent interference may reflect baseline error, or an error in
the baseline, as the baseline does not reflect background noise.
Thus, persistent interference may be mitigated by relaxing the
baseline as described below in reference to FIG. 4.
[0075] However, if the first self-capacitive measurements and the
second self-capacitive measurements are inconsistent, then
intermittent interference is detected. In such a scenario,
adjusting the baseline to account for such interference would cause
present input objects to not be detected or non-existent input
objects to be detected. Thus, mitigation for intermittent
interference may be performed. Techniques to mitigate for
intermittent interference may be to change a frequency of
self-capacitive sensing, repetitively perform self-capacitive
sensing to obtain consistent self-capacitive measurements, or
perform other operations to mitigate for the intermittent
interference.
[0076] FIG. 4 show a flowchart in accordance with one or more
embodiments of the disclosure. While the various steps in this
flowchart are presented and described sequentially, some or all of
the steps may be executed in different orders, may be combined or
omitted, and some or all of the steps may be executed in parallel.
Furthermore, the steps may be performed actively or passively. For
example, some steps may be performed using polling or be interrupt
driven in accordance with one or more embodiments of the invention.
By way of an example, determination steps may not require a
processor to process an instruction unless an interrupt is received
to signify that condition exists in accordance with one or more
embodiments of the invention. As another example, determination
steps may be performed by performing a test, such as checking a
data value to test whether the value is consistent with the tested
condition in accordance with one or more embodiments of the
invention.
[0077] The steps shown in FIG. 4 may be performed in combination
with the steps shown in FIG. 3. Further, some of the steps may be
omitted. Similarly, only some steps shown in FIG. 4 may be added to
FIG. 3.
[0078] In Step 401, mutual capacitive sensing is performed to
obtain mutual capacitive measurements. In Step 403, self-capacitive
sensing is performed to obtain self-capacitive measurements. Mutual
capacitive sensing and self-capacitive sensing may be performed as
discussed above in reference to FIGS. 2 and 3.
[0079] In Step 405, the self-capacitive measurements and the mutual
capacitive measurements are compared. The self-capacitive
measurements and the mutual capacitive measurements may be compared
as discussed above in reference to FIG. 3.
[0080] In Step 407, a determination is made whether an
inconsistency is detected between the self-capacitive measurements
and the mutual capacitive measurements in accordance with one or
more embodiments of the disclosure. Detecting an inconsistency may
be performed as discussed above in reference to FIG. 3.
[0081] If an inconsistency is not detected, then the flow may
proceed to Step 409. In Step 409, the system continues to perform
capacitive sensing on subsequent frames. In particular, the
processing circuitry continues to process the current frame, such
as to perform moisture detection and mitigation, low-ground mass
detection and mitigation, and other operations, and obtains
positional information. The processing circuitry may send the
positional information to a host, an application, central
processing unit, etc., and the host may perform an action based on
the positional information. Similarly, the sensor circuitry may
continue to perform frames of sensing. Further, the flow of FIG. 4
may repeat for each frame of sensing.
[0082] Returning to Step 407, if an inconsistency is detected
between the self-capacitive measurements and the mutual capacitive
measurements, if not in a repeat cycle (described below), the
subsequent frame of sensing is halted to obtain current
self-capacitive measurements by performing self-capacitive sensing.
Triggering the halt and obtaining current self-capacitive
measurements may be performed as discussed above in reference to
FIGS. 2 and 3.
[0083] In Step 413, the current self-capacitive measurements are
compared with an immediate preceding self-capacitive measurements
in accordance with one or more embodiments of the disclosure. The
most recently obtained self-capacitive measurements are compared
with the immediately preceding obtained self-capacitive
measurements to check for consistency in accordance with one or
more embodiments of the disclosure. Comparing the self-capacitive
measurements may be performed as discussed above with reference to
FIG. 3.
[0084] In Step 415, a determination is made whether an
inconsistency is detected between the self-capacitive measurements
compared in Step 413. Detecting an inconsistency is performed as
discussed above with reference to FIG. 3. If an inconsistency is
not detected, the flow proceeds to Step 417. In particular, the
processing system may consider the inconsistency between
self-capacitive measurements and mutual capacitive measurements as
persistent interference.
[0085] In Step 417, in one or more embodiments, baseline error
mitigation is performed based on detecting a baseline error. For
example, fast relaxation or accelerated relaxation of one or more
of the self-capacitive baselines and mutual capacitive baseline may
be performed. Relaxation changes the values of the baseline for
each current sensing frame by a defined amount to be closer to the
measurements of the current sensing frame. Thus, if the
measurements in several sensing frames are the exact same, then
over a predefined period of time, the baseline values will be the
same as the measurements over the sensing frames. However, if the
measurement values over the sensing frames change, then the
baseline values may adjust to be closer to the measurement values
without matching any sensing frame's measurement values. Other
baseline error mitigation techniques or persistent interference
techniques may alternatively or additionally be performed without
departing from the scope of the disclosure.
[0086] Returning to Step 415, if an inconsistency is detected
between self-capacitive measurements, the flow may proceed to Step
419. In Step 419, a determination is made whether to repeat as part
of a repeat cycle. The repeat cycle repetitively obtains
self-capacitive measurements until the self-capacitive measurements
are consistent with the mutual capacitive measurements or with each
other. For example, in a scenario in which repetitive intermittent
interference exists, the processing system may continue to obtain
self-capacitive measurements until such self-capacitive
measurements do not exhibit intermittent interference or until a
predefined number of attempts at obtaining such self-capacitive
measurements has elapsed. For example, the pre-defined number of
attempts may be three.
[0087] If a determination is made to repeat, the flow proceeds to
Step 423 to start the repeat cycle. In Step 423, current
self-capacitive measurements are obtained by performing
self-capacitive sensing in accordance with one or more embodiments
of the disclosure. In a repeat cycle, the sensor circuitry may be
halted from a prior iteration in one or more embodiments and a new
trigger to halt the sensor circuitry is not sent. In other
embodiments, the sensor circuitry immediately continues operating
to obtain the next frame after obtaining the current
self-capacitive measurements for the processing circuitry. In such
a scenario, the processing circuitry may trigger the sensor
circuitry to halt and obtain current self-capacitive measurements
in a repeat cycle. The self-capacitive measurements obtained in
Step 423 are compared in Step 405 with the mutual capacitive
measurements, and if inconsistent, compared in Step 413, with the
immediate preceding self-capacitive measurements. Optionally, if
the processing system is in a repeat cycle, the comparison in Step
413 may be several sets of self-capacitive measurements obtained
for the current frame, in Step 411, and part of the repeat cycle.
The repeat cycle may include obtaining self-capacitive measurements
in using different frequencies to modulate the sensing signals.
Each set of self-capacitive measurements may be obtained using a
different sensing frequency than each other set of self-capacitive
measurements. By varying the sensing frequency, a sensing frequency
that is not subject to intermittent interference or as much
intermittent interference may be identified.
[0088] Continuing with FIG. 4, if a determination is made not to
repeat, the flow may proceed to Step 421. In Step 421 interference
mitigation is performed based on detecting intermittent
interference. For example, the interference mitigation may be to
change the sensing frequency of the sensing signals for the
absolute capacitive sensing. Other techniques for intermittent
interference mitigation may be performed without departing from the
scope of the disclosure.
[0089] As shown above, by halting the next frame of sensing and
obtaining absolute capacitive measurements, the sets of absolute
capacitive measurements compared may be temporally close to each
other such that the state of the sensing region does not change
between absolute capacitive sensing. Thus, intermittent
interference may be detected. By detecting intermittent
interferences, intermittent interference may be mitigated. By
distinguishing intermittent interference from persistent
interference and not attempting to correct intermittent
interference using techniques for correcting persistent
interference, one or more embodiments may be able to better detect
the presence of actual input objects in the sensing region, thereby
improving the operation of the input device.
[0090] Thus, the embodiments and examples set forth herein were
presented in order to best explain the present disclosure and the
particular application and to thereby enable those skilled in the
art to make and use the disclosure. However, those skilled in the
art will recognize that the foregoing description and examples have
been presented for the purposes of illustration and example only.
The description as set forth is not intended to be exhaustive or to
limit the disclosure to the precise form disclosed.
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